Data Scientist – Environmental Engineering

This is a fully remote position, open to applicants in United States.

📋 Description

• Create, develop, and implement advanced analytics and machine learning models to address water and environmental challenges.

• Recognize and articulate AI and ML opportunities within the water and wastewater sector.

• Construct and implement models, generative and agentic AI solutions, web applications, and geospatial analyses.

• Assist in the development and deployment of cloud-based applications for both internal and external users.

• Perform exploratory data analysis, model creation, statistical evaluation, feature extraction, and hyperparameter optimization.

• Establish data storage solutions, preprocess data, and generate data visualizations.

• Develop and enhance machine learning models.

• Adhere to DevOps, software engineering, version control, and best practices for model deployment.

• Collaborate with cross-functional and multidisciplinary project teams to ascertain data requirements.

• Communicate findings to internal stakeholders and aid in client-facing presentations.

• Keep abreast of industry trends and research developments in machine learning and applications within the water sector.

• Represent Brown and Caldwell at conferences and through technical publications.

• Provide mentorship and share knowledge with less experienced team members as required.

• Undertake additional tasks as needed based on evolving requirements.

⛳️ Requirements

• At least 2 years of experience in Data Science or a related field.

• Usually certified in the SMS Framework and advancing through SMS competencies.

• Strong programming capabilities in Python and R.

• Proficient in relevant libraries and frameworks.

• Ability to develop clean, maintainable, and scalable code with minimal supervision.

• Basic understanding of water, wastewater, environmental engineering, and scientific topics.

• Degree in computer science, engineering, or a related discipline, or equivalent experience.

• High proficiency in Python, pandas, NumPy, scikit-learn, and SQL.

• Experience in developing and deploying generative AI applications, retrieval systems, and agentic workflows.

• Background in building data-driven applications, APIs, web tools, and interactive user interfaces.

• Familiarity with cloud-based solutions, DevOps, Azure, DevSecOps, and MLOps.

• Experience with Azure Machine Learning Studio, Azure Databricks, Azure Synapse Analytics, and Azure Cognitive Services/OpenAI API integration.

• Proven experience in developing data-processing workflows for ML algorithms.

• Knowledge of regression, clustering, random forests, gradient boosting, neural networks, and statistics.

• Experience with TensorFlow and PyTorch.

• Understanding of software engineering principles, Git, and production-ready code.

• Familiarity with CI/CD for ML, such as GitHub Actions or Azure DevOps.

• Experience with streaming data processing and time-series forecasting for IoT and edge computing.

• Proficiency in cloud infrastructure and web application development.

• Experience with geospatial data processing, spatial analysis, and interactive mapping.

• Ability to engage clients, understand their needs, and position data-driven consulting solutions.

• Strong problem-solving abilities and capacity to work collaboratively across various functions.

• Excellent communication skills, adept at interacting with both technical and non-technical stakeholders.

• Willingness to remain updated with trends in data science and environmental engineering.

• Subject to a pre-employment background check and drug screening.

🏝️ Benefits

• Medical, dental, and vision insurance.

• Short- and long-term disability insurance.

• Life insurance.

• Employee assistance program.

• Paid time off.

• Parental leave.

• Paid holidays.

• 401(k) retirement savings plan with employer matching.

• Eligibility for performance-based bonuses.

• Employee referral bonuses.

• Tuition reimbursement.

• Pet insurance.

• Long-term care insurance.

• Exceptional opportunities for professional development.